Arbitragex Amazon FBA Calculator (Amazon.de)

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (read-only, idempotent, non-destructive), so the description's job is to add calculation behavior. It does: the fee is derived from length/width/height/weight when fba_fee is absent, and country VAT plus category-based referral fees are applied. It doesn't discuss rounding, currency of output, or error conditions, keeping it below 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The core capability and scope appear in the first clause, followed by the fallback-fee behavior. The German sentence is then repeated in English, which is somewhat redundant but short and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 14 parameters and no output schema, the description correctly names the return values (profit, margin, ROI, break-even buy price) and the fee model, which is the key information an agent needs. Minor gaps remain around surcharges (lithium, CEP, EFN) which are only visible in the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all 14 parameters are already documented, including the fba_fee precedence. The description restates the fba_fee/lithium/CEP logic at a high level but adds no syntax or format detail beyond the schema. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (profit, margin, ROI and break-even buy price calculation) plus the exact scope (Amazon DE/FR/IT/ES FBA). An agent can tell it apart from the sibling estimate_fba_fee, which only computes the fee component, without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives one conditional usage rule — fba_fee overrides the dimensional calculation when supplied — which is useful. But it never states when to choose this tool over estimate_fba_fee or get_amazon_referral_fee, nor when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the read-only annotations, the description discloses the rate-card effective date, country tariffs, surcharge percentages, CEP, EFN, DE high-season treatment, and low-price tariff conditions. These are substantive behavioral details an agent needs to interpret the calculation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the fee calculation and appropriately dense for a 10-parameter pricing tool. The single long German sentence is somewhat run-on, but almost every clause conveys relevant rate-card behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the calculation target, marketplaces, rate period, and major conditional surcharges/programs, which is substantial for a complex fee tool with no output schema. It could be slightly stronger by explicitly stating the returned unit/currency and rounding assumptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds meaningful relationships, especially that the low-price tariff requires both sale_price and category, and it contextualizes EFN and CEP inputs beyond the individual schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific calculation: net FBA shipping fee per unit for DE/FR/IT/ES based on Amazon's official rate card. It clearly distinguishes this from referral-fee and profit-calculation siblings by focusing narrowly on the FBA fulfilment fee.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when conditional inputs apply, such as sale_price and category for the low-price tariff, CEP, EFN, and DE high season. It does not explicitly name alternatives or say when not to use this versus calculate_amazon_fba_profit, but the usage context is otherwise clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior. The description adds useful calculation context by saying the fee is net and includes tiered, minimum, and closing fee components, though it does not describe the return shape or currency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loads the core purpose and fee components. The English sentence largely duplicates the German sentence, so it is efficient but not maximally concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple three-parameter calculator with full schema coverage and safety annotations, the description covers the computation scope and included fee components. Without an output schema, it could be more explicit about the returned fee format or currency, but it is otherwise sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all three parameters, including category enum, gross EUR sale_price, and default DE marketplace. The description adds net-vs-gross context for the fee but does not add parameter-specific constraints or syntax beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource as an Amazon referral fee for a given price, category, and marketplace, including tiered, minimum, and closing fee components. It is distinct from FBA fee/profit siblings by fee type, but it does not explicitly name or differentiate against those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied: calculate the referral fee for a price in an Amazon category on DE/FR/IT/ES. The description does not state when to use this instead of estimate_fba_fee or calculate_amazon_fba_profit, nor does it give exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds real context beyond that: it discloses the data provenance (Amazon-Tarifübersicht 'Gebühren für Europa') and pins the marketplace coverage to DE/FR/IT/ES, which tells the agent this is a static regional snapshot. It does not mention result size or whether the list is complete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The scope and content are front-loaded in the first clause, which is good. However the trailing English sentence largely re-translates the German one, so a meaningful share of the text is redundant rather than additive.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-optional-param lookup with no output schema, the description gives enough: what is returned (Schlüssel, Gebührenregel), for which marketplaces, and that filtering exists. Only the shape/size of the returned category list is left unstated, which is a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the single optional 'search' param is documented with an example ('Elektronik'). The description only restates that filtering is optional; it adds no matching semantics (substring vs exact, case handling). Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Liste aller Amazon-Kategorien') plus the two payload fields an agent gets back (Schlüssel und Gebührenregel) and the exact marketplace scope (DE/FR/IT/ES). It is clearly the enumeration tool, distinct from the single-fee siblings like get_amazon_referral_fee, without needing the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The only usage cue is 'Optional nach Stichwort filtern', which implies when to supply the search parameter. There is no statement of when this tool should be preferred over get_amazon_referral_fee or estimate_fba_fee, and no exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the read-only/idempotent/non-destructive profile, so the description's job is to add context — and it does: it discloses that no-slug returns an index of articles and that content is German. It doesn't describe article length or structure, but that is minor given the safety hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, the mode-switching behavior front-loaded after the topic list. The parenthetical topic enumeration is somewhat long but serves as useful scope-setting rather than filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description correctly compensates by telling the agent what it gets back in each mode (article vs. list) and in which language. Sufficient for a single-optional-param read tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with an enum of the ten valid slugs, so the schema carries most weight. The description adds value by explaining the semantics of omission ('Ohne slug: Liste der Artikel'), which the schema's 'Artikel (optional)' does not spell out.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete resource (seller guides) with an enumerated topic list, and clarifies that omitting the slug yields an article list. It is clearly distinguishable from the sibling fee/calculator tools, though the verb 'read' is only implied by the name rather than restated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Ohne slug: Liste der Artikel' gives an explicit condition for the two modes of use (list vs. fetch one article). It does not, however, mention when an agent should prefer calculate_amazon_fba_profit or estimate_fba_fee over consulting a guide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.